[{"_1":2,"_151":-5,"_152":-5},"loaderData",{"_3":4,"_13":14,"_20":21,"_130":131},"root",{"_5":-5,"_6":-7,"_7":8,"_9":-7,"_10":11,"_12":-7},"currentUser","primaryEmail","siteVerification","6LeIxAcTAAAAAJcZVRqyHh71UMIEGNQ_MXjiZKhI","toast","enableDev",false,"incidentStatus","routes/_layout",{"_15":-5,"_16":17,"_18":17,"_19":11},"username","isAskGordonEnabled",true,"isUsingNewTemplate","showMinimalLanding","routes/_layout.r.$namespace.$reponame",{"_22":23,"_24":-5,"_25":11,"_26":11,"_27":28,"_29":30,"_31":-5,"_32":11,"_33":34,"_83":-5,"_84":85,"_123":-5,"_124":11,"_125":17,"_126":11,"_127":-5,"_128":129},"canonicalUrl","https://hub.docker.com/r/padhi/excelsynth/tags","mcpServer","canSeeDockerfile","canSeeAutobuilds","namespace","padhi","reponame","excelsynth","cloudBuildSource","isAutobuildsAvailable","repo",{"_35":36,"_37":38,"_40":41,"_42":43,"_44":11,"_45":46,"_47":48,"_49":50,"_52":30,"_27":28,"_53":54,"_55":39,"_56":57,"_58":59,"_60":61,"_62":-5,"_63":57,"_64":65,"_66":11,"_67":28,"_68":69,"_74":11,"_75":76,"_80":28,"_81":82},"categories",[],"content_types",[39],"image","date_registered","2020-02-25T11:13:21.324401Z","description","","is_private","last_updated","2020-06-19T01:45:54.947584Z","last_modified","2024-10-16T13:48:34.145251Z","media_types",[51],"application/vnd.docker.container.image.v1+json","name","pull_count",213,"repository_type","star_count",0,"status",1,"status_description","active","source","collaborator_count","full_description","ExcelSynth\n

\n==========\n\n[![](https://img.shields.io/travis/SaswatPadhi/ExcelSynth/master.svg?logo=travis&style=popout&label=Travis+Build)][travis]\n \n[![](https://img.shields.io/docker/cloud/build/padhi/excelsynth.svg?logo=docker&style=popout&label=Docker+Image)][docker-hub]\n\nAn enumerative synthesizer for recovering Excel formulas from CSVs.\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n

\n Input: CSV File\n (samples/example.csv)\n \n Output: Formula Mask\n

\n Input: CSV File\n (samples/example.csv)\n	\n Output: Formula Mask\n
\n _{\n \nCol 1 , Col 2 , Col 3 , Col 4 , Col 5\nRow 2 , 1. , 10. , 9.5 , 24.\nRow 3 , 23. , 12. , 0.5 , 35.\nRow 4 , 22. , 2. , -9. , 24.\nRow 5 , -1. , 6. , 6.5 , 5.\nRow 6 , 59. , 0. , -29.5 , 41.\nRow 7 , 11. , -2. , -7.5 , 9.\nRow 8 , 115. , 14. , -43.5 , 23.\n \n}\n	\n _{\n \n , , , ,\n , , , =(C2-(B2/(1.+1.)) ,\n , , , =(C3-(B3/(1.+1.)) ,\n , , , =(C4-(B4/(1.+1.)) ,\n , , , =(C5-(B5/(1.+1.)) ,\n , , , =(C6-(B6/(1.+1.)) ,\n , , , =(C7-(B7/(1.+1.)) ,\n , =SUM(B2:B7) , =(SUM(C2:C7)/(1.+1.)) , =(C8-(B8/(1.+1.)) , =AVERAGE(E2:E7)\n \n}\n

\n _{\n \nCol 1 , Col 2 , Col 3 , Col 4 , Col 5\nRow 2 , 1. , 10. , 9.5 , 24.\nRow 3 , 23. , 12. , 0.5 , 35.\nRow 4 , 22. , 2. , -9. , 24.\nRow 5 , -1. , 6. , 6.5 , 5.\nRow 6 , 59. , 0. , -29.5 , 41.\nRow 7 , 11. , -2. , -7.5 , 9.\nRow 8 , 115. , 14. , -43.5 , 23.\n \n}\n

\n _{\n \n , , , ,\n , , , =(C2-(B2/(1.+1.)) ,\n , , , =(C3-(B3/(1.+1.)) ,\n , , , =(C4-(B4/(1.+1.)) ,\n , , , =(C5-(B5/(1.+1.)) ,\n , , , =(C6-(B6/(1.+1.)) ,\n , , , =(C7-(B7/(1.+1.)) ,\n , =SUM(B2:B7) , =(SUM(C2:C7)/(1.+1.)) , =(C8-(B8/(1.+1.)) , =AVERAGE(E2:E7)\n \n}\n

\n\n----\n\n## Installation\n\n0. [Get `docker` for your OS](https://docs.docker.com/install).\n1. Pull the docker image^[#](#note_1): `docker pull padhi/excelsynth`.\n2. Run a container over the image: `docker run -it padhi/excelsynth`.
\n This would give you a `bash` shell within ExcelSynth directory.\n3. To run ExcelSynth on `samples/unit_test.csv`, execute: `dune exec bin/App.exe -- samples/unit_test.csv`\n4. To run the unit tests, execute: `dune runtest`\n\n^# Alternatively, you could also build the Docker image locally:\n\n```bash\ndocker build -t padhi/excelsynth github.com/SaswatPadhi/ExcelSynth\n```\n\n## Usage\n\n### Formula Synthesis from CSV\n\n```text\n$ dune exec bin/App.exe -- -h\nSynthesize Excel formulas for a CSV file.\n\n App.exe [flag] ... FILENAME\n\n=== flags ===\n\n [-check-last-col-aggregations BOOLEAN] synthesize aggregation formulas for\n cells in the last column\n [-check-last-row-aggregations BOOLEAN] synthesize aggregation formulas for\n cells in the last row\n [-check-pointwise-col-operations BOOLEAN] synthesize pointwise\n transformations for columns\n [-check-pointwise-row-operations BOOLEAN] synthesize pointwise\n transformations for rows\n [-constant FLOAT] ... additional Boolean/numeric/string\n constants\n [-disable-constant-solutions BOOLEAN] disable constant formulas (e.g.\n =0.0) for cells\n [-enable-2d-aggregation BOOLEAN] use 2D ranges in aggregation\n operations\n [-enable-booleans BOOLEAN] enable Boolean and conditional\n expressions\n [-log-path FILENAME] enable logging and output to the\n specified path\n [-mask-path FILENAME] a known formula mask for the CSV\n file\n [-max-expr-size INTEGER] maximum cost (AST size) of\n expressions to explore\n [-max-threads INTEGER] maximum number of threads to create\n [-range STRING] a range (in RC:R'C' format) that\n bounds the synthesis space\n [-relative-error FLOAT] the fractional relative error\n allowed in float comparisons\n [-restrict-to-top-left-data BOOLEAN] only use data to the top left of a\n cell in formulas\n [-type-error-threshold FLOAT] maximum fraction of cells that may\n be ignored due to type errors\n [-value-error-threshold FLOAT] maximum fraction of cells that may\n be ignored due to value errors\n```\n\n### Bulk Processing ([`scripts/evaluate.sh`](scripts/evaluate.sh))\n\nThe following **input** directory structure is required:\n\n```text\n\n |\n +-- table_ranges.csv <--- Contains table ranges for CSV files\n |\n +-- evaluated_csvs <--- Contains fully evaluated CSV files\n | |\n | +-- .csv\n | |\n | `-- .csv\n |\n +-- formula_csvs <--- Contains CSV files with formulas\n |\n +-- .csv\n |\n `-- .csv\n```\n\nThe following **output** data is generated within this directory:\n\n```text\n\n |\n : · · ·\n |\n : · · ·\n |\n +-- extracted_masks <--- Contents generated by scripts/extract_mask.py\n | |\n | +-- .csv <--- Ground truth mask from `../formula_csvs/.csv`\n | |\n | `-- .csv\n |\n +-- recovered_masks <--- Contents generated by scripts/recover_mask.py\n | |\n | +-- Baseline <--- Unrestricted synthesis (over whole sheet)\n | | |\n | | +-- .csv <--- Synthesized mask from `../evaluated_csvs/.csv`\n | | |\n | | `-- .csv\n | |\n : : · · ·\n | |\n | `-- <--- Synthesis restricted to tables from \n | |\n | +-- .csv <--- Synthesized mask from `../evaluated_csvs/.csv`\n | |\n | `-- .csv\n |\n `-- comparison_masks <--- Contents generated by scripts/compare_masks.py\n |\n +-- full <--- All cells within a recovered mask are checked\n | |\n | +-- Baseline <--- Evaluation of unrestricted-synthesis masks\n | | |\n | | +-- .csv <--- Evaluation of `../recovered_masks/Baseline/.csv`\n | | |\n | | `-- .csv\n | |\n : : · · ·\n | |\n | `-- <--- Evaluation of restricted-synthesis masks\n | |\n | +-- .csv\n | |\n | `-- .csv\n |\n `-- in-table <--- Only in-table cells are checked\n |\n +-- Baseline\n | |\n | +-- .csv\n | |\n | `-- .csv\n |\n : · · ·\n |\n `-- \n |\n +-- .csv\n |\n `-- .csv\n```\n\n#### Extract A Formula Masks from CSVs\n\n```text\n$ python3 scripts/extract_mask.py -h\nusage: extract_mask.py [-h] -i INPUT_DIR -o OUTPUT_DIR\n\noptional arguments:\n -h, --help show this help message and exit\n\n -i INPUT_DIR, --input-dir INPUT_DIR\n -o OUTPUT_DIR, --output-dir OUTPUT_DIR\n\n$ python3 scripts/extract_mask.py -i data/formula_csvs -o data/extracted_masks\n```\n\n#### Recover Formula Masks from CSVs\n\n```text\n$ python3 scripts/recover_mask.py -h\nusage: recover_mask.py [-h] -e EVAL_CSV_DIR -o OUTPUT_DIR -c TABLE_RANGE_COLUMN\n tables_data_csv\n\npositional arguments:\n tables_data_csv\n\noptional arguments:\n -h, --help show this help message and exit\n\n -e EVAL_CSV_DIR, --eval-csv-dir EVAL_CSV_DIR\n -o OUTPUT_DIR, --output-dir OUTPUT_DIR\n -c TABLE_RANGE_COLUMN, --table-range-column TABLE_RANGE_COLUMN\n\n$ python3 scripts/recover_mask.py -e data/evaluated_csvs -o data/recovered_masks \\\n -c 1 data/table_ranges.csv\n```\n\n`tables_data_csv` has extracted table ranges in `TABLE_RANGE_COLUMN` (0-indexed).\n\n#### Compare Formula Masks\n\n```text\n$ python3 scripts/compare_masks.py -h\nusage: compare_masks.py [-h] -g GROUND_TRUTH_DIR -p PREDICTION_DIR -o OUTPUT_DIR\n\noptional arguments:\n -h, --help show this help message and exit\n\n -g GROUND_TRUTH_DIR, --ground-truth-dir GROUND_TRUTH_DIR\n -p PREDICTION_DIR, --prediction-dir PREDICTION_DIR\n -o OUTPUT_DIR, --output-dir OUTPUT_DIR\n\n$ python3 scripts/compare_mask.py -g data/extracted_masks \\\n -p data/recovered_masks/table_detector_1 \\\n -o data/comparison_masks/table_detector_1\n```\n\n[docker-hub]: https://hub.docker.com/r/padhi/excelsynth\n[travis]: 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padhi/excelsynth

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